A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
A mechanism to share risks and costs with guarantees against extreme outcomes.
We consider a class of participation rights, i.e. obligations issued by a company to investors who are interested in performance-based compensation. Albeit having desirable economic properties equity-based debt obligations (EbDO) pose challenges in accounting and contract pricing. We formulate and solve the associated …
The study analyzes pricing and hedging of STCDOs using an affine model with a catastrophic risk component.
The stability of the financial system is associated with systemic risk factors such as the concurrent default of numerous small obligors. Hence it is of utmost importance to study the mutual dependence of losses for different creditors in the case of large, overlapping credit portfolios. We analytically calculate the m…
This paper considers mutual obligations in the interconnected bank system and analyzes their influence on joint and marginal survival probabilities as well as CDS and FTD prices for the individual banks. To make the role of mutual obligations more transparent, a simple structural default model with banks' assets driven…
The paper examines how CoCo bonds can enhance financial stability in interconnected banking systems.
The paper examines clearing payments in financial networks to prevent cascaded defaults.
PCA simplifies multivariate extreme data analysis.
In this paper we extend recent breakthrough of Chen-Cheng \cite{CC1, CC2, CC3} on existence of constant scalar Kähler metric on a compact Kähler manifold to Calabi's extremal metric. Our argument follows \cite{CC3} and there are no new a prior estimates needed, but rather there are necessary modifications adapted to th…
Financial institutions face new model risks with AI, requiring enhanced model risk management.
GARCH-UGH improves VaR estimation for financial risk management.
Reinsurance counterparty credit risk (RCCR) is the risk of a loss arising from the fact that a reinsurance company is unable to fulfill her contractual obligations towards the ceding insurer. RCCR is an important risk category for insurance companies which, so far, has been addressed mostly via qualitative approaches. …
The grid integration of intermittent Renewable Energy Sources (RES) causes costs for grid operators due to forecast uncertainty and the resulting production schedule mismatches. These so-called profile service costs are marginal cost components and can be understood as an insurance fee against RES production schedule u…
The interbank market is considered one of the most important channels of contagion. Its network representation, where banks and claims/obligations are represented by nodes and links (respectively), has received a lot of attention in the recent theoretical and empirical literature, for assessing systemic risk and identi…
Networked-guarantee loans may cause the systemic risk related concern of the government and banks in China. The prediction of default of enterprise loans is a typical extremely imbalanced prediction problem, and the networked-guarantee make this problem more difficult to solve. Since the guaranteed loan is a debt oblig…
Credit and liquidity risks represent main channels of financial contagion for interbank lending markets. On one hand, banks face potential losses whenever their counterparties are under distress and thus unable to fulfill their obligations. On the other hand, solvency constraints may force banks to recover lost funding…
Quantum computing speeds up CDO pricing models.
Study examines dependence of extreme electricity prices in Australian markets.
We analyse the effectiveness of modern deep learning techniques in predicting credit ratings over a universe of thousands of global corporate entities obligations when compared to most popular, traditional machine-learning approaches such as linear models and tree-based classifiers. Our results show a adequate accuracy…
A new method reduces uncertainty in predicting rare extreme events without assuming their presence in training data.
We present a model that investigates the spontaneous emergence of randomness in equity market microstructure. The phase space analysis of our model exposes an endogenous source of fluctuation in price and volume. We formulate a control problem for maximizing price regularity and stability while minimizing entanglement …
Network analysis improves risk assessment for surety bonds.
APLC-XLNet improves XMTC by clustering labels and reducing computational time.
Study supports conjecture about pretzel links' homology.
Extreme classification seeks to assign each data point, the most relevant labels from a universe of a million or more labels. This task is faced with the dual challenge of high precision and scalability, with millisecond level prediction times being a benchmark. We propose DEFRAG, an adaptive feature agglomeration tech…
Proves uniqueness of certain spacetime solutions with extremal horizons.
Much has been said lately about entrepreneurship, so it seems important to leave here some personal analysis on this topic. The issues outlined here result from a work in about a year in which because a personal and professional obligations it was doing some research on these issues. This is an interesting topic that h…
We prove that on a Kähler manifold admitting an extremal metric and for any Kähler potential close to , the Calabi flow starting at exists for all time and the modified Calabi flow starting at will always be close to . Furthermore, when the initial data is invariant under t…
AGCA approximates angular variation on the unit sphere, reducing extremal dependence problems to eigenanalysis.
Extremal Kahler metrics and Sasaki-Einstein metrics characterized via coercive energy.
Anomaly-aware forecast improves accuracy for extreme events.
xVAE models extreme turbulence events in turbulent flows.
This paper provides a general framework for modeling financial contagion in a system with obligations in multiple illiquid assets (e.g., currencies). In so doing, we develop a multi-layered financial network that extends the single network of Eisenberg and Noe (2001). In particular, we develop a financial contagion mod…
This paper optimizes portfolio compression by reducing excess notional in market contracts.
In this paper, we extend the work in \cite{D}\cite{ChrusLiWe}\cite{ChrusCo}\cite{Co}. We weaken the asymptotic conditions on the second fundamental form, and we also give an norm bound for the difference between general data and Extreme Kerr data or Extreme Kerr-Newman data by proving convexity of the renormali…
Paper introduces Cycles Protocol to integrate trade credit into market clearing.
Paper introduces adversarial lossy compression for video artifacts reduction.
The study examines how alternative resource adequacy contract designs affect market participants' risk profiles and resource mix.
This paper considers the modelling of collateralized debt obligations (CDOs). We propose a top-down model via forward rates generalizing Filipović, Overbeck and Schmidt (2009) to the case where the forward rates are driven by a finite dimensional Lévy process. The contribution of this work is twofold: we provide condit…
We present a novel distribution-free approach, the data-driven threshold machine (DTM), for a fundamental problem at the core of many learning tasks: choose a threshold for a given pre-specified level that bounds the tail probability of the maximum of a (possibly dependent but stationary) random sequence. We do not ass…
Modeling house prices in Australia reveals supply limitations as the primary driver of extreme trends.
Extreme classification problems are multiclass and multilabel classification problems where the number of outputs is so large that straightforward strategies are neither statistically nor computationally viable. One strategy for dealing with the computational burden is via a tree decomposition of the output space. Whil…
The problem of existence of arbitrage free and monotone CDO term structure models is studied. Conditions for positivity and monotonicity of the corresponding Heath-Jarrow-Morton-Musiela equation for the -forward rates with the use of the Milian type result are formulated. Two state spaces are taken into account - of…
We show that metrics that maximize the k-th Steklov eigenvalue on surfaces with boundary arise from free boundary minimal surfaces in the unit ball. We prove several properties of the volumes of these minimal submanifolds. For free boundary minimal submanifolds in the ball we show that the boundary volume is reduced up…
Paper examines risk measure expansions under FGM dependence, improving accuracy at extreme levels.
Study optimizes climate adaptation strategies for NYC.
This paper is devoted to the study of the max K-armed bandit problem, which consists in sequentially allocating resources in order to detect extreme values. Our contribution is twofold. We first significantly refine the analysis of the ExtremeHunter algorithm carried out in Carpentier and Valko (2014), and next propose…
Arora, Barak, Brunnermeier, and Ge showed that taking computational complexity into account, a dishonest seller could strategically place lemons in financial derivatives to make them substantially less valuable to buyers. We show that if the seller is required to construct derivatives of a certain form, then this pheno…